A presence-only model of suitable roosting habitat for the endangered Indiana bat in the southern Appalachians

Abstract

We know little about how forest bats, which are cryptic and mobile, use roosts on a landscape scale. For widely distributed species like the endangered Indiana bat Myotis sodalis, identifying landscape-scale roost habitat associations will be important for managing the species in different regions where it occurs. For example, in the southern Appalachian Mountains, USA, M. sodalis roosts are scattered across a heavily forested landscape, which makes protecting individual roosts impractical during large-scale management activities. We created a predictive spatial model of summer roosting habitat to identify important predictors using the presence-only modeling program MaxEnt and an information theoretic approach for model comparison. Two of 26 candidate models together accounted for >0.93 of AICc weights. Elevation and forest type were top predictors of presence; aspect north/ south and distance-to-ridge were also important. The final average best model indicated that 5% of the study area was suitable habitat and 0.5% was optimal. This model matched our field observations that, in the southern Appalachian Mountains, optimal roosting habitat for M. sodalis is near the ridge top in south-facing mixed pine-hardwood forests at elevations from 260–575 m. Our findings, coupled with data from other studies, suggest M. sodalis is flexible in roost habitat selection across different ecoregions with varying topography and land use patterns. We caution that, while mature pine-hardwood forests are important now, specific areas of suitable and optimal habitat will change over time. Combining the information theoretic approach with presence-only models makes it possible to develop landscape-scale habitat suitability maps for forest bats.

  • Citation: Hammond, K.R.; O’Keefe, J.M.; Aldrich, S.P.; Loeb, S.C. 2016. A presence-only model of suitable roosting habitat for the endangered Indiana bat in the southern Appalachians. PLoS ONE 11(4): e0154464. doi:10.1371/journal.pone.0154464
  • Posted Date: May 10, 2016
  • Modified Date: October 24, 2016
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